Funding & M&A

C
Showing 1–30 of 109
  • arXiv cs.AI (Artificial Intelligence) · EN Inference & Efficiency
    Subquadratic Attention with a Hierarchical Tree-Structured Indexer
    Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    PersonaChatBench: Evaluating Chat Assistants with Diverse Simulated Users
    Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Empirical Evaluation of Quantum Kernel Methods for Classification: A Comparative Study with Classical Kernels
    Machine Learning Neural Network Software Engineering
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Inference & Efficiency
    When Does Test-Time Search Help World Action Models? An Empirical Audit of Candidate Selection and Simulator Integrity
    Inference Neural Network Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    WASABI: Wasserstein Sampling via Bridge Interpolants
    Neural Network Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN Funding & M&A
    Chronos-2: A foundation model for multivariate time series forecasting
    Neural Network Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Multimodal
    Sensorium: An Open-Source Multimodal Data Collection and Curation Library for Embodied Surgical AI
    Deep Learning Neural Network
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Observable-Specific Validity Tests for Scientific AI: Controlled Approximations and Intervention Response
    Gemini Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    SimXAI: A Simple Drop-in Layer Increases Interaction Quality and Understanding in Conversational XAI
    AI Agents Deep Learning Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    DIFFNAS: Predictor-Free Neural Architecture Search via Diffusion Model and Zero-Cost Evaluation
    Neural Network Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Continual Reinforcement Learning Is an Integration Problem
    AI Agents Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN Funding & M&A
    Backpropagation-free Deep Learning for Time-Series Classification
    Deep Learning Neural Network Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Training & Fine-tuning
    Implicit Assumptions About Tasks in Continual Learning
    Neural Network Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Training & Fine-tuning
    Different Models, Shared Failures: Auditing Frozen-Encoder Pools for Medical Segmentation
    Fine-tuning Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN Funding & M&A
    Leakage-Controlled Structure-Preserving Augmentation and Template-Aware Evaluation for Bangla Symptom-Based Disease Prediction
    Neural Network
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Policy & Regulation
    From Training Exposure to Membership Evidence: A Controlled Study of OLMo 2
    Inference Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    GraphNIAH: A Benchmark for Long-Context Reasoning over Real-World Graphs
    Deep Learning Gemini GPT Neural Network Software Engineering
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • Microsoft Research Blog · EN Developer Tools
    From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence
    Microsoft Research uses synthetic enterprise data to evaluate Copilot
    Microsoft Neural Network
    Microsoft Research says evaluating Copilot at enterprise scale needs test data that captures real organizational complexity, yet real enterprise data holds sensitive information that can never be used for evaluation. The post describes using synthetic enterprise data to build confidence in Copilot.
    Read original (Microsoft Research Blog) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    TSBPO: Tree-Structured Branching for Policy Optimization in Interactive Language Agents
    AI Agents Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • ITmedia AI+ · JA New Model Releases
    キオクシア中間決算「過去最高」連呼　純利益2.2兆円、初の配当実施　AI需要で「成長さらに加速」
    Kioxia posts record H1 net profit of 2.2T yen, first dividend
    Kioxia Holdings reported interim results for the fiscal year ending March 2027, with net profit of 2.2 trillion yen. Its three-month second quarter alone exceeded the prior full-year revenue, and AI demand is expected to accelerate growth further. It will pay its first dividend since listing.
    Read original (ITmedia AI+) ↗
  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    A prospective randomized study of patient-centered AI for clinical visit preparation
    Google
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Comparative Evaluation of LLM-Based Review Paradigms for Academic Paper Quality Assessment
    Neural Network
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • Cohere Blog · EN Funding & M&A
    Cohere advances C$4 billion commitment to strengthen Canada’s AI leadership and significantly expand its national workforce
    Cohere expands Canada pledge: C$4B+ and 1,500 jobs by 2031
    Neural Network Reinforcement Learning
    Cohere expanded its Canadian commitments, now expecting over 1,500 jobs and C$4 billion-plus in R&D and AI infrastructure through 2031. At least 1,000 roles will be in research and engineering, aimed at turning Canadian talent into products.
    Read original (Cohere Blog) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    Elucidating the Design Space of LM Data Attribution
    Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Funding & M&A
    Luggage re-identification: A study of strategies towards a real-world application
    Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    When to Assist and What to Suggest: Joint Gating and Memory-Grounded Hint Generation in One Compact Decoder
    Llama
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Agents & Tool Use
    Pre-Crime for Agents, at the Last Second: Probing When a Recruited Agent Gives In
    AI Agents GPT Neural Network
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Multi-View MoE: Letting Every Router Shape Expert Computation
    Deep Learning Mixture of Experts (MoE)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.LG (Machine Learning) · EN Funding & M&A
    Machine Learning-Based Detection of Mobile Money Scan Messages in Ghana: A Comparative Evaluation of Naive Bayes, Support Vector Machine, and Randon Forest Classifiers
    AI Agents Machine Learning Neural Network Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    TRACER, a time-to-event EHR foundation model for disease detection across health systems
    Read original (arXiv cs.LG (Machine Learning)) ↗